Abstract:
We are developing a new computing environment for geodetic image processing for Interferometric Synthetic Aperture Radar (InSAR) sensors to enable scientists to reduce measurements from radar satellites and aircraft directly to new geophysical products without first requiring them to develop detailed expertise in radar processing and without the need for centralized processing centers and radar engineers to bring Level-0 raw radar data up to Level-3 data products. The NRC Decadal Survey-recommended DESDynI mission will deliver directly to the science community data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystem. Our InSAR Scientific Computing Environment, applied to a global data set such as from DESDynI, enables a new class of analyses at time and spatial scales unavailable using current approaches.

We are implementing an accurate, extensible, and modular processing system and reworking the processing approach in order to i) enable multi-scene analysis by adding new algorithms, ii) permit user-reconfigurable operation and extensibility, and iii) capitalize on codes already developed by NASA and the science community. The framework incorporates modern programming methods, including rigorous componentization of processing codes, abstraction and generalization of data models, and a robust, intuitive user interface with graduated exposure to the levels of sophistication, allowing novices to apply it readily for common tasks and experienced users to mine data with great facility and flexibility. The framework is designed to easily allow user contributions, creating an open source community that will extend the framework into the indefinite future.